#libraries used 
library(vegan)
library(betapart)
library(psych)
library(ggplot2)
library(ggthemes)
library(ggnewscale)
library(gridExtra)
library(knitr)
library(patchwork)

#plot code 
#split violin plot for variable:abundance  
abund_wrap<-ggplot(metadataMossType, aes(x=reorder(epiphytesep,-abundance), y=log10(abundance),fill=newFactor,color=newFactor))+
introdataviz::geom_split_violin(alpha=.6,trim = FALSE)+
 stat_summary(fun.data = "mean_se", geom = "pointrange",size=0.25, show.legend = F, 
               position = position_dodge(.4)) +
labs(x = element_blank(),y=(bquote("(B) "~log[10]~Density/25~cm^2~{})))+
scale_color_manual(values=c("#5D8852","#6D92B1","#477567","#6EA161","#87B4DA","#70A08F"),guide="none")+
scale_fill_manual(values=c("#7FB069","#90C2E7","#477567","#92CE7B","#9FDDF7","#70A08F"),guide="none")+
theme_tufte()+
theme(plot.title = element_text(size = 13, family = "Times", face = "bold"),
  text = element_text(size = 12, family = "Times"),
  axis.title = element_text(face="bold"),
  axis.text.x=element_text(size = 10),
  axis.text.y=element_text(size = 10),
  strip.text = element_text(face="bold"))+
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),panel.background = element_rect( size = 1, linetype = "solid"))+
theme(legend.position ="none")

#split violin plot for variable:richness  
rich_wrap<-ggplot(metadataMossType, aes(x=reorder(epiphytesep,-abundance), y=richness,fill=newFactor,color=newFactor))+
introdataviz::geom_split_violin(alpha=.6,trim = FALSE)+
 stat_summary(fun.data = "mean_se", geom = "pointrange",size=0.25, show.legend = F, 
               position = position_dodge(.4)) +
labs(x = element_blank(),y=(bquote("(A) "~Richness/25~cm^2~{})))+
scale_color_manual(values=c("#5D8852","#6D92B1","#477567","#6EA161","#87B4DA","#70A08F"),guide="none")+
scale_fill_manual(values=c("#7FB069","#90C2E7","#477567","#92CE7B","#9FDDF7","#70A08F"),guide="none")+
theme_tufte()+
theme(plot.title = element_text(size = 13, family = "Times", face = "bold"),
  text = element_text(size = 12, family = "Times"),
  axis.title = element_text(face="bold"),
  axis.text.x=element_text(size = 10),
  axis.text.y=element_text(size = 10),
  strip.text = element_text(face="bold"))+
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),panel.background = element_rect( size = 1, linetype = "solid"))+
theme(legend.position ="none")

#split violin plot for variable:diversity  
div_wrap<-ggplot(metadataMossType, aes(x=reorder(epiphytesep,-abundance), y=diversity,fill=newFactor,color=newFactor))+
introdataviz::geom_split_violin(alpha=.6,trim = FALSE)+
 stat_summary(fun.data = "mean_se", geom = "pointrange", size=0.25,show.legend = F, 
               position = position_dodge(.4)) +
labs(x = element_blank(),y=(bquote("(C) "~Diversity/25~cm^2~{})))+
scale_color_manual(values=c("#5D8852","#6D92B1","#477567","#6EA161","#87B4DA","#70A08F"),guide="none")+
scale_fill_manual(values=c("#7FB069","#90C2E7","#477567","#92CE7B","#9FDDF7","#70A08F"),guide="none")+
theme_tufte()+
theme(plot.title = element_text(size = 13, family = "Times", face = "bold"),
  text = element_text(size = 12, family = "Times"),
  axis.title = element_text(face="bold"),
  axis.text.x=element_text(size = 10),
  axis.text.y=element_text(size = 10),
  strip.text = element_text(face="bold"))+
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),panel.background = element_rect( size = 1, linetype = "solid"))+
theme(legend.position ="none")

#combine plots
Violin <- (abund_wrap | rich_wrap | div_wrap)

Violin

#packages used 
library(vegan)
library(betapart)
library(psych)
library(ggplot2)
library(ggthemes)

#plot code 
Ordination=ggplot(NMDSord, aes(x=MDS1, y=MDS2))+
geom_point(aes(color=metadataMossType$newFactor, fill=metadataMossType$newFactor,shape=factor(metadataMossType$newFactor)),size=2.5)+
scale_fill_manual(values=alpha(c("#477567","#5D8852","#6D92B1","#70A08F","#6EA161","#87B4DA"),.6),
  name ="Sample",
  breaks=c("corridorSkirt","corridorBole","corridorLichen","shelterwoodSkirt","shelterwoodBole","shelterwoodLichen"),
  labels=c("Corridor Basal","Corridor Bole","Corridor Lichen","Shelterwood Basal","Shelterwood Bole","Shelterwood Lichen"))+
scale_color_manual(values=c("#477567","#5D8852","#6D92B1","#70A08F","#6EA161","#87B4DA"),
  name ="Sample",
  breaks=c("corridorSkirt","corridorBole","corridorLichen","shelterwoodSkirt","shelterwoodBole","shelterwoodLichen"),
  labels=c("Corridor Basal","Corridor Bole","Corridor Lichen","Shelterwood Basal","Shelterwood Bole","Shelterwood Lichen"))+
new_scale("color")+
scale_shape_manual(values=c(21,21,21,24,24,24),
  name="Sample",breaks=c("corridorSkirt","corridorBole","corridorLichen","shelterwoodSkirt","shelterwoodBole","shelterwoodLichen"),
  labels=c("Corridor Basal","Corridor Bole","Corridor Lichen","Shelterwood Basal","Shelterwood Bole","Shelterwood Lichen"))+
stat_ellipse(size=1,aes(x = MDS1,y=MDS2,color=metadataMossType$epiphytesep,linetype=factor(metadataMossType$standType)))+
scale_linetype_discrete(name="Treatment", labels=c("Corridor","Shelterwood"))+
scale_color_manual(values=c("#477567","#7FB069","#90C2E7"),name="Epiphyte", breaks=c("Basal","Bole","Lichen"),labels=c("Basal","Bole","Lichen"))+
labs(x="NMDS 1", y="NMDS 2")+
theme_bw()+
theme(plot.title = element_text(size = 15, family = "Times", face = "bold"),text = element_text(size = 12, family = "Times"),axis.title = element_text(face="bold"),axis.text.x=element_text(size = 10),panel.grid.major = element_blank(),panel.grid.minor = element_blank(),panel.border = element_blank())+ 
theme(legend.justification=c(1,1), legend.position=c(1,1))+
theme(legend.background = element_rect(fill = "transparent"),legend.key = element_rect(fill = "transparent", color = NA))+
xlim(NA,11)+theme(panel.background = element_rect(fill = "transparent",colour = "transparent"))+ 
theme(plot.background = element_rect(fill = "transparent"))+
 theme(legend.key.height= unit(.5, 'cm'),
        legend.key.width= unit(.5, 'cm'))

Ordination

#packages used 
library(DESeq2)
library(ggplot2)
library(ggthemes)
library(scales)
library(patchwork)
library(gridExtra)
library(MetBrewer)
library(dplyr)

#Plot code 
PCA=ggplot(euPCA,aes(PC1,PC2,col=tissue,shape=rep,fill=tissue))+
geom_point(size=4)+
scale_color_manual(name="Tissue",labels=c("Trachea","Midgut","Malpighian tubule"),values=c("#718038","#A33B20","#BC7D38"),limits=c("trach","malTube","gut"))+
scale_fill_manual(name="Tissue",labels=c("Trachea","Midgut","Malpighian tubule"),values=c("#718038","#A33B20","#BC7D38"),limits=c("trach","malTube","gut"))+
scale_shape_manual(name="Replicate",labels=c("1","2","3"),values=c(21,22,24),limits=c("1","2","3"))+
theme_few()+
theme(plot.title = element_text(size = 12, family = "Times", face = "bold"),
  text = element_text(size = 12, family = "Times"),
  axis.title = element_text(face="bold",size=12),
  axis.text.x=element_text(size = 12),
  axis.text.y=element_text(size = 12),
  strip.text = element_text(face="bold"))+
theme(legend.title = element_text(size = 12, face = "bold"),text=element_text(size =12, family = "Times"))+
theme(legend.position=c(.9,.3))+
guides(color=guide_legend(order=2),fill=guide_legend(order=2),shape=guide_legend(order=1))+
theme(legend.background = element_rect(fill = "transparent"),legend.key = element_rect(fill = "transparent", color = NA))+
theme(panel.background = element_rect(fill = "transparent",colour = "transparent"))+ 
theme(plot.background = element_rect(fill = "transparent"))

PCA

#plot code 
#pairwise 1 
euc_volcano_MT <- ggplot(data=euc_deMT5_DF, aes(x=log2FoldChange, y=-log10(pvalue), col=diffexpressed2)) + geom_point(alpha=0.75) + theme_few() + 
geom_vline(xintercept=c(-2, 2), col="#8d642c") +
geom_hline(yintercept=-log10(0.05), col="#8d642c")+
labs(title="Trachea v Malpighian Tubules",x= element_blank(),y= element_blank()) +
theme(plot.title = element_text(size = 13, family = "Tahoma", face = "bold"),
  text = element_text(size = 12, family = "Tahoma"),
  axis.title = element_text(face="bold"),
  axis.text.x=element_text(size = 13),
  axis.text.y=element_text(size = 13),
  strip.text = element_text(face="bold"))+
scale_color_manual(name="",labels=c("Up","Down","No"), values=c("#718038","#A33B20","#D2CAC5"),limits=c("UP","DOWN","NO"))+
ylim(NA,130)+
xlim(-30,30)+
theme(legend.position=c(.8,.8))

#pairwise 2
euc_volcano_GI <- ggplot(data=euc_deGI5_DF, aes(x=log2FoldChange, y=-log10(pvalue), col=diffexpressed2)) + geom_point(alpha=0.75) + theme_few() + 
geom_vline(xintercept=c(-2, 2), col="#8d642c") +
geom_hline(yintercept=-log10(0.05), col="#8d642c")+
labs(title="Trachea v Midut",x= element_blank(),y= element_blank()) + 
theme(plot.title = element_text(size = 13, family = "Tahoma", face = "bold"),
  text = element_text(size = 12, family = "Tahoma"),
  axis.title = element_text(face="bold"),
  axis.text.x=element_text(size = 13),
  axis.text.y=element_text(size = 13),
  strip.text = element_text(face="bold"))+
scale_color_manual(name="",labels=c("Up","Down","No"), values=c("#718038","#BC7D38","#D2CAC5"),limits=c("UP","DOWN","NO"))+
ylim(NA,130)+
xlim(-30,30)+
theme(legend.position=c(.8,.8))

#combine 
Volcano <- euc_volcano_MT + euc_volcano_GI 

Volcano

#libraries used 
library(ggplot2)
library(ggthemes)
library(gridExtra)
library(patchwork)
library(MetBrewer)
library(tidyverse)
library(cowplot)

#plot code 
#plot identity of BLAST hit (x-axis) and length of hit divided by length of query (y-axis)
id_by_length <- ggplot(geneContent,aes(x=percIdent,y=percSeq,fill=class,color=class)) + 
geom_point(shape=21,alpha=0.65,size=2.3) + 
labs(x="Percent identity of BLAST hit",y="BLAST hit length / query length") + 
scale_color_manual(values=met.brewer('Moreau',16),
  name ="Class",
  breaks=c("carbonicAnhydrase","channel_Cl","channel_K","channel_water","cuticularProtein","DEGENaC_pickpocket","exchanger_CPA","exchanger_other","NaKatpase_subunit","receptor_CAPA","receptor_leukokinin","receptor_serotonin","Resilin","vatpaseSubunit","V0_domain"),
  labels=c("Carbonic anhydrase",expression(paste("Cl"^"-","channel")),expression(paste("K"^"+","channel")),"Water channel","Cuticular protein","Pickpocket gene","CPA exchanger","Other exchanger",expression(paste("Na"^"+","K"^"+","ATPase subunit")),"CAPA receptor","Leukokinin receptor","Serotonin receptor","Resilin",expression(paste("Vacuolar H"^"+","ATPase subunit")),"V0 domain"))+
scale_fill_manual(values=met.brewer('Moreau',16),
  name ="Class",
  breaks=c("carbonicAnhydrase","channel_Cl","channel_K","channel_water","cuticularProtein","DEGENaC_pickpocket","exchanger_CPA","exchanger_other","NaKatpase_subunit","receptor_CAPA","receptor_leukokinin","receptor_serotonin","Resilin","vatpaseSubunit"),
  labels=c("Carbonic anhydrase",expression(paste("Cl"^"-","channel")),expression(paste("K"^"+","channel")),"Water channel","Cuticular protein","Pickpocket gene","CPA exchanger","Other exchanger",expression(paste("Na"^"+","K"^"+","ATPase subunit")),"CAPA receptor","Leukokinin receptor","Serotonin receptor","Resilin",expression(paste("Vacuolar H"^"+","ATPase subunit"))))+
theme_few() +
  theme(
  text = element_text(size = 10, family = "sans"),
  axis.title = element_text(face="bold"),
  axis.text.x=element_text(size = 10),
  axis.text.y=element_text(size = 10),
  strip.text = element_text(face="bold"))+ 
 theme(legend.title = element_text(
      family = "sans",size = 8),legend.text=element_text(family = "sans",size = 6))+
 theme(legend.text.align = 0)+
 theme(legend.key.height= unit(.35, 'cm'),
        legend.key.width= unit(.5, 'cm'))

#generate histograms of percent identity and of length of hit divided by length of query
#id 
id_hist <- ggplot(data=geneContent,aes(x=percIdent)) + 
geom_histogram(binwidth=5,color="#A1A18A",fill="#A1A18A",alpha=0.7) + 
labs(x="Percent identity of BLAST hit",y=element_blank())+
theme_few()+
theme(plot.title = element_text(size = 12, family = "sans", face = "bold"),
  text = element_text(size = 10, family = "sans"),
  axis.title = element_text(face="bold"),
  axis.text.x=element_text(size = 10),
  axis.text.y=element_text(size = 10),
  strip.text = element_text(face="bold"))

#length
length_hist <- ggplot(data=geneContent,aes(x=percSeq)) + 
geom_histogram(binwidth=.05,color="#e3b577",fill="#e3b577",alpha=0.7) + 
labs(x="BLAST hit length / query length",y=element_blank())+
theme_few()+
theme(plot.title = element_text(size = 12, family = "sans", face = "bold"),
  text = element_text(size = 10, family = "sans"),
  axis.title = element_text(face="bold"),
  axis.text.x=element_text(size = 10),
  axis.text.y=element_text(size = 10),
  strip.text = element_text(face="bold"))

#compile into one plot
id_grid <- plot_grid(id_hist,length_hist)
Histogram <- plot_grid(id_grid,id_by_length,ncol=1)

Histogram

#packages
library(ggplot2)
library(ggthemes)
library(rphylopic)

#plot code - base 
lowPlot <- ggplot(HLES6, aes(x = (1-habitatRemaining), y = percentSurvive, color = taxon, fill = taxon))+
theme_tufte() +
geom_point() +
geom_smooth() +
scale_fill_manual(values=c("#8491A3","#B78B5A","#6D213C","#95BF73","#2F4C38"),
  name ="Taxon",
  breaks=c("neogastropods","spider","ants","stylo","diplopoda"),
  labels=c("Neogastropods","Spiders","Ants","Stylommatophorans","Diplopods"))+
scale_color_manual(values=c("#8491A3","#B78B5A","#6D213C","#95BF73","#2F4C38"),
  name ="Taxon",
  breaks=c("neogastropods","spider","ants","stylo","diplopoda"),
  labels=c("Neogastropods","Spiders","Ants","Stylommatophorans","Diplopods"))+
labs(x= "Proportion of habitat destroyed", y="Proportion of habitat surviving",title = "Proportion of taxa surviving vs proportion of habitat destroyed")+
theme(plot.title = element_text(size = 14, family = "Tahoma", face = "bold"),
  text = element_text(size = 12, family = "Tahoma"),
  axis.title = element_text(face="bold"),
  axis.text.x=element_text(size = 12),
  axis.text.y=element_text(size = 12),
  strip.text = element_text(face="bold"))+ 
xlim(0.5,0.95)+
 theme(legend.position =c(0.2,0.2))+
 theme(legend.title = element_text(
      family = "Tahoma",size = 10))

#add phylopics
ant_uuid <- get_uuid(name = "formicoids")
neo_uuid <- get_uuid(name = "Tricolia pullus")
stylo_uuid <-get_uuid(name = "Myosotella myosotis")
dip_uuid <- get_uuid(name = "Myriapoda")
spi_uuid <- get_uuid(name = "Liphistius desultor")

#add silhouettes to plot
LoWeSS=lowPlot + 
add_phylopic(uuid = ant_uuid,  x = .94, y = .42, height = .043, fill="#6D213C") + 
add_phylopic(uuid =neo_uuid,  x = .94, y = .6, height = .072, fill="#8491A3") +
add_phylopic(uuid =stylo_uuid,  x = .94, y = .32, height = .077, fill="#95BF73") + 
add_phylopic(uuid =dip_uuid,  x = .94, y = .25, height = .049, fill="#2F4C38") +
add_phylopic(uuid =spi_uuid,  x = .94, y = .49, height = .073, fill="#B78B5A") 

LoWeSS

#packages used 
library(ggplot2)
library(patchwork)
library(ggthemes)

# boxplot 1 
fig1a <- ggplot(allDists10and100_nd, aes(x=as.character(dimension), y=dists,fill=as.character(steps),color=as.character(steps)))+
geom_boxplot(width = .6, alpha=.6,show.legend = FALSE)+
scale_x_discrete(name="Dimensionality",labels=c("1d","2d","4d","8d","16d","32d"),limits =c("1","2","4","8","16","32"))+
scale_y_continuous(name="Euclidean distance", limits = c(-10, 120))+
scale_color_manual(name = "Random walk flavor \nand time steps", values=c("#96C886","#53782B"),limits=c("10","100"), labels = c("Ten steps, simple", "100 steps, simple"),guide="none")+ 
scale_fill_manual(name = "Random walk flavor \nand time steps", values=c("#96C886","#53782B"),limits=c("10","100"), labels = c("Ten steps, simple", "100 steps, simple"),guide = guide_legend(override.aes = list(shape = 15)))+
theme_classic()+
theme(plot.title = element_text(size = 10, family = "sans", face = "bold"), 
  text = element_text(size = 8, family = "sans"),
  axis.title = element_text(face="bold"),
  axis.text.x=element_text(size = 8),
  axis.text.y=element_text(size = 8),
  strip.text = element_text(face="bold"))+
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),panel.background = element_rect( size = 1, linetype = "solid"))+
theme(legend.position=c(0.15,0.82), legend.title = element_text(size=7)) + 
theme(legend.key.size = unit(0.3, 'cm'))+ 
ggtitle(" Figure 1a: \n Euclidean distance after 10 or 100 steps \n on integer lattices of different dimensionalities \n (simple random walks)")

#boxplot 2
fig1b <- ggplot(allDists_n1d_10and100, aes(x=as.character(dimension), y=dists,fill=as.character(steps),color=as.character(steps)))+
geom_boxplot(width = .6, alpha=.6,show.legend = FALSE)+
scale_x_discrete(name="Dimensionality",labels=c("1d","2d","4d","8d","16d","32d"),limits =c("1","2","4","8","16","32"))+
scale_y_continuous(name="Euclidean distance", limits = c(-10, 120))+
scale_color_manual(name = "Random walk flavor \nand time steps", values=c("#B594B6","#664176"),limits=c("10","100"), labels = c("Ten steps, n 1d", "100 steps, n 1d"),guide="none")+
scale_fill_manual(name = "Random walk flavor \nand time steps", values=c("#B594B6","#664176"),limits=c("10","100"), labels = c("Ten steps, n 1d", "100 steps, n 1d"),guide = guide_legend(override.aes = list(shape = 15)))+
theme_classic()+
theme(plot.title = element_text(size = 10, family = "sans", face = "bold"),
  text = element_text(size = 8, family = "sans"),
  axis.title = element_text(face="bold"),
  axis.text.x=element_text(size = 8),
  axis.text.y=element_text(size = 8),
  strip.text = element_text(face="bold"))+
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),panel.background = element_rect( size = 1, linetype = "solid"))+
theme(legend.position=c(0.15,0.82), legend.title = element_text(size=7)) + 
theme(legend.key.size = unit(0.3, 'cm'))+
ggtitle(" Figure 1b: \n Euclidean distance after 10 or 100 steps \n on integer lattices of different dimensionalities \n N 1d Random Walks")

#boxplot 3 
fig1c <- ggplot(allDists10_ndn1d, aes(x=as.character(dimension), y=dists,fill=as.character(flavor),color=as.character(flavor)))+
geom_boxplot(width = .6, alpha=.6,show.legend = FALSE)+
scale_x_discrete(name="Dimensionality",labels=c("1d","2d","4d","8d","16d","32d"),limits =c("1","2","4","8","16","32"))+
scale_y_continuous(name="Euclidean distance", limits = c(-10, 120))+
scale_color_manual(name = "Random walk flavor \nand time steps", values=c("#96C886","#B594B6"),limits=c("nd","n1d"), labels = c("Ten steps, simple", "Ten steps, n 1d"),guide="none")+
scale_fill_manual(name = "Random walk flavor \nand time steps", values=c("#96C886","#B594B6"),limits=c("nd","n1d"), labels = c("Ten steps, simple", "Ten steps, n 1d"),guide = guide_legend(override.aes = list(shape = 15)))+
theme_classic()+
theme(plot.title = element_text(size = 10, family = "sans", face = "bold"),
  text = element_text(size = 8, family = "sans"),
  axis.title = element_text(face="bold"),
  axis.text.x=element_text(size = 8),
  axis.text.y=element_text(size = 8),
  strip.text = element_text(face="bold"))+
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),panel.background = element_rect( size = 1, linetype = "solid"))+
theme(legend.position=c(0.15,0.82), legend.title = element_text(size=7)) + 
theme(legend.key.size = unit(0.3, 'cm'))+
ggtitle(" Figure 1c: \n Euclidean distance after 10 steps \n on integer lattices of different dimensionalities \n nD random walks vs. N 1d random walks")

#boxplot 4
fig1d <- ggplot(allDists100_ndn1d, aes(x=as.character(dimension), y=dists,fill=as.character(flavor),color=as.character(flavor)))+
geom_boxplot(width = .6, alpha=.6,show.legend = FALSE)+
scale_x_discrete(name="Dimensionality",labels=c("1d","2d","4d","8d","16d","32d"),limits =c("1","2","4","8","16","32"))+
scale_y_continuous(name="Euclidean distance", limits = c(-10, 120))+
scale_color_manual(name = "Random walk flavor \nand time steps", values=c("#53782B","#664176"),limits=c("nd","n1d"), labels = c("100 steps, simple", "100 steps, n 1d"),guide="none")+
scale_fill_manual(name = "Random walk flavor \nand time steps", values=c("#53782B","#664176"),limits=c("nd","n1d"), labels = c("100 steps, simple", "100 steps, n 1d"),guide = guide_legend(override.aes = list(shape = 15)))+
theme_classic()+
theme(plot.title = element_text(size = 10, family = "sans", face = "bold"),
  text = element_text(size = 8, family = "sans"),
  axis.title = element_text(face="bold"),
  axis.text.x=element_text(size = 8),
  axis.text.y=element_text(size = 8),
  strip.text = element_text(face="bold"))+
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.background = element_rect( size = 1, linetype = "solid"))+
theme(legend.position=c(0.15,0.82), legend.title = element_text(size=7)) + 
theme(legend.key.size = unit(0.3, 'cm'))+
ggtitle(" Figure 1d: \n Euclidean distance after 100 steps \n on integer lattices of different dimensionalities \n nD random walks vs. N 1d random walks")

Boxplots=(fig1a | fig1b) / (fig1c | fig1d)

Boxplots

#packages used 
library(ggplot2)
library(tidyverse)
library(ggthemes)
library(ggridges)

#plot code 
Ridgeline=ggplot(hungerALL_3, aes(x = distFromDmasech, y = species_lumped, color =
geoGrp, fill = geoGrp)) +
geom_density_ridges(
    jittered_points = TRUE, scale = .95, rel_min_height = .01,
    point_shape = "|", point_size = 3, size = 0.25,
    position = position_points_jitter(height = 0)) +
scale_fill_manual(name = "geographical \n group", 
  values=c("#96CAAC","#175676","#512D38","#A47963","#A6A57A"))+
scale_color_manual(name = "geographical \n group", 
  values=c("#96CAAC","#175676","#512D38","#A47963","#A6A57A"))+
scale_y_discrete(limits = c("chilorhytis", "ringens", "loxodonta", "crenata", "goniobasis", "pyramis", "inflatula", "papilio", 
  "triplochilus", "eurystoma", "nodulosa", "omphaloptyx", "elegantissima", "polymorpha", "nudicollum", "lutea", "spinoscapula", 
  "robiginosa", "subalata", "fragilipennis", "pelewensis", "crassilabris", "alata", "lamellata", "aurea", "microbasodonta",
"basodonta", "aspera", "pteropurpuroides", "rudicostata", "expansilabris", "unisulcata", "echinata")) +
ylab("species") +
xlab("distance from Dmasech (m)")+
theme(text = element_text(size = 11, family = "sans"),
  axis.text.y=element_text(size = 9,family="sans",face="italic"),
  axis.ticks.y=element_blank(),
  axis.text.x=element_text(size = 9,family="sans"),
  legend.text=element_text(size=8,family="sans"),legend.title = element_text(size=8))+
theme(panel.background = element_blank(),panel.grid.major.y = element_line(color = "#D3D3D3",size = 0.25))

Ridgeline

#packages used 
library(sf)
library(mapview)
library(osmdata)
library(scatterpie)

Scatter=ggplot() + 
  geom_sf(data = chelbacheb_coastline$osm_lines, 
  inherit.aes = FALSE, 
  color = "black", 
  size = 0.1) + 
  geom_scatterpie(aes(x=long, y=lat), 
  data= localityClusts_localityGroupSummaries,
     cols=c("asAirai", "asKoror", "asNgeruktabel", "asSouthern", "asMixed"),  
     alpha = 0.9, pie_scale = 0.7,color=NA) + 
  scale_fill_manual(name = "cluster", 
  values=scatterColours,labels = c("Airai", "Koror","Ngeruktabel","Southern","Mixed"))+
theme_minimal()+
theme(text = element_text(size = 11, family = "sans"),
  axis.ticks.y=element_blank(),
  axis.text.x=element_text(size = 9,family="sans"),
  legend.text=element_text(size=8,family="sans"),legend.title = element_text(size=8))+
theme(panel.background = element_blank(),panel.grid.major.y = element_line(color = "#D3D3D3",size = 0.25))

Scatter